35 citations · 82 across the 23 of their papers we have counts for
5 papers · 1 filter
From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization
Catarina G. Belem, Pouya Pezeshkpour, Hayate Iso +3
Although many studies have investigated and reduced hallucinations in large language models (LLMs) for single-document tasks, research on hallucination in multi-document summarizat…
Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data
Seiji Maekawa, Hayate Iso, Nikita Bhutani
The rapid increase in textual information means we need more efficient methods to sift through, organize, and understand it all. While retrieval-augmented generation (RAG) models e…
A Blueprint Architecture of Compound AI Systems for Enterprise
Eser Kandogan, Sajjadur Rahman, Nikita Bhutani +11
Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases. Towards this goa…
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models
Seiji Maekawa, Hayate Iso, Sairam Gurajada +1
While large language models (LMs) demonstrate remarkable performance, they encounter challenges in providing accurate responses when queried for information beyond their pre-traine…
AmbigNLG: Addressing Task Ambiguity in Instruction for NLG
Ayana Niwa, Hayate Iso
We introduce AmbigNLG, a novel task designed to tackle the challenge of task ambiguity in instructions for Natural Language Generation (NLG). Ambiguous instructions often impede th…